Search results

1 – 10 of over 9000
To view the access options for this content please click here
Article
Publication date: 6 February 2017

Shanshan Zhang, Zhiqiang Wang, Xiande Zhao and Min Zhang

The purpose of this paper is to empirically investigate the effects of institutional support on product and process innovation and firm performance and describe how…

Abstract

Purpose

The purpose of this paper is to empirically investigate the effects of institutional support on product and process innovation and firm performance and describe how dysfunctional competition influences relevant outcomes.

Design/methodology/approach

This study develops a research model based on institution-based view and tests it using structural equation modeling and empirical data collected from 300 manufacturers in China.

Findings

The results show that institutional support positively affects product and process innovation and firm performance. Both product and process innovation improve firm performance. The findings reveal that dysfunctional competition significantly reduces the positive effects of institutional support on product and process innovation but leaves the effects of institutional support and product and process innovation on firm performance unaffected.

Originality/value

This study contributes to innovation literature by providing insights into the impact of China’s institutional environment on manufacturing firms’ product and process innovation decisions. The findings also contribute to institution-based view literature by providing empirical evidence on the joint effects of institutional support and dysfunctional competition on product and process innovation and firm performance. This study can help manufacturers in China take advantage of institutional environment and adjust product and process innovation decisions accordingly.

Details

Industrial Management & Data Systems, vol. 117 no. 1
Type: Research Article
ISSN: 0263-5577

Keywords

To view the access options for this content please click here

Abstract

Details

Sport Business in Leading Economies
Type: Book
ISBN: 978-1-78743-564-3

To view the access options for this content please click here
Article
Publication date: 20 June 2017

Changjun Chen, Yang Li, Min Zhang, Xiaonan Wang, Chao Zhang and Hemin Jing

Additive manufacturing (AM), a method used in the nuclear, space and racing industries, allows the creation of customized titanium alloy scaffolds with highly defined…

Abstract

Purpose

Additive manufacturing (AM), a method used in the nuclear, space and racing industries, allows the creation of customized titanium alloy scaffolds with highly defined external shape and internal structure using rapid prototyping as supporting external structures within which bone tissue can grow. AM allows porous tantalum parts with mechanical properties close to that of bone tissue to be obtained.

Design/methodology/approach

In this paper, porous tantalum structures with different scan distance were fabricated by AM using laser multi-layer micro-cladding.

Findings

Porous tantalum samples were tested for resistance to compressive force and used scanning electron microscope to reveal the morphology of before and after compressive tests. Their structure and mechanical properties of these porous Ta structures with porosity in the range of 35.48 to 50 per cent were investigated. The porous tantalum structures have comparable compressive strength 56 ∼ 480 MPa, and elastic modulus 2.8 ∼ 9.0GPa, which is very close to those of human spongy bone and compact bone.

Research limitations/implications

This paper does not demonstrate the implant results.

Practical implications

It can be used as implant material for the repair bone.

Social implications

It can be used for fabrication of other porous materials.

Originality/value

This paper system researched the scan distance on how to influence the mechanical properties of fabricated porous tantalum structures.

Details

Rapid Prototyping Journal, vol. 23 no. 4
Type: Research Article
ISSN: 1355-2546

Keywords

To view the access options for this content please click here
Article
Publication date: 20 July 2020

Longwei Wang, Meige Song, Min Zhang and Li Wang

This study aims to empirically investigate the role of contracts in tacit knowledge acquisition in research and development (R&D) alliances. By combining the perspectives…

Abstract

Purpose

This study aims to empirically investigate the role of contracts in tacit knowledge acquisition in research and development (R&D) alliances. By combining the perspectives of sensemaking and transaction cost economics (TCE), this study proposes a model about the mechanisms through which shared goals and contract completeness jointly affect tacit knowledge acquisition.

Design/methodology/approach

This study adopted a quantitative design and used the questionnaire survey method to collect data. The authors finally collected data on 196 R&D alliance samples in China. Multiple regression analysis was used to test the hypotheses.

Findings

There is strong empirical support that contract completeness has a positive effect on shared goals and that shared goals have a positive effect on tacit knowledge acquisition. Meanwhile, contract completeness weakens the positive effect of shared goals on tacit knowledge acquisition. Therefore, this study reveals that contract completeness has an inverted U-shaped effect on tacit knowledge acquisition.

Practical implications

The findings suggest that managers should consider both the psychological and rational effects of contract governance simultaneously, thus recognizing the importance of a moderate level of contract completeness for tacit knowledge acquisition in R&D alliances.

Originality/value

This study enhances the current understanding of contract governance by integrating the sensemaking and TCE perspectives. The findings provide a possible explanation of how contracts affect tacit knowledge acquisition in R&D alliances. The authors expand the research on contract governance and alliance knowledge acquisition by revealing the inverted U-shaped relationship between contract governance and tacit knowledge acquisition.

Details

Journal of Knowledge Management, vol. 25 no. 5
Type: Research Article
ISSN: 1367-3270

Keywords

To view the access options for this content please click here
Article
Publication date: 10 January 2020

Qiuping Huang, Xiande Zhao, Min Zhang, KwanHo Yeung, Lijun Ma and Jeff Hoi-yan Yeung

The purpose of this paper is to empirically investigate the joint effects of lead time, information sharing and the accounts receivable period on reverse factoring (RF…

Abstract

Purpose

The purpose of this paper is to empirically investigate the joint effects of lead time, information sharing and the accounts receivable period on reverse factoring (RF) adoption from the suppliers’ perspective.

Design/methodology/approach

Supported by one of the largest commercial banks in China, survey data are collected from 424 Chinese manufacturing firms and analyzed using regression methods.

Findings

The results suggest that lead time positively affects suppliers’ RF adoption directly and indirectly through the accounts receivable period. Meanwhile, information sharing has a positive, direct and a negative, indirect influence on suppliers’ RF adoption.

Originality/value

The findings give suppliers and financial institutions a better understanding of how to leverage the benefits of RF.

Details

Industrial Management & Data Systems, vol. 120 no. 1
Type: Research Article
ISSN: 0263-5577

Keywords

To view the access options for this content please click here
Article
Publication date: 1 April 2021

Min Zhang, Qiuping Huang, Xiande Zhao and Lijun Ma

In this study, we examine the implementation of purchase order finance (POF) which is an innovative supply chain finance (SCF) solution by an innovative SCF lender (i.e…

Abstract

Purpose

In this study, we examine the implementation of purchase order finance (POF) which is an innovative supply chain finance (SCF) solution by an innovative SCF lender (i.e. supply chain service provider (SCSP)). The effect of information integration between the SCSP (lender) and product designers (borrowers) on the lender's POF decisions and the borrowers' new product launch is investigated.

Design/methodology/approach

We conduct a case study in the Chinese smartphone industry. A mixed methods design is used, and data are collected from both the supply chain service provider (SCSP) and product designers. We first conduct a qualitative study. Hypotheses are developed concerning the relationships between information integration, in terms of social interaction and information system integration, POF and new product launch. We then conduct a quantitative study. The multilevel structural equation modelling method is used to test the hypotheses.

Findings

We find that information system integration is positively associated with POF but has no significant effect on new product launch. Social interaction is negatively associated with POF but positively associated with new product launch. POF is positively associated with new product launch.

Originality/value

This study contributes to the literature by empirically examining the implementation of POF from both the lender's and borrower's perspectives. We find that information system integration and social interaction have different effects on POF and new product launch. The results thus provide insights into how a lender makes POF decisions and reveal the benefits of POF for borrowers.

Details

International Journal of Operations & Production Management, vol. 41 no. 4
Type: Research Article
ISSN: 0144-3577

Keywords

To view the access options for this content please click here
Article
Publication date: 25 January 2021

Min Zhang, Yunxiao Xue, Jun Yang and Yan Zhang

Members' knowledge contribution behavior has positive significance for maintaining the activity of the knowledge community, as well as for improving knowledge interaction…

Abstract

Purpose

Members' knowledge contribution behavior has positive significance for maintaining the activity of the knowledge community, as well as for improving knowledge interaction efficiency and member viscosity. With the development of the mobile Internet, knowledge communities based on social platforms have become more convenient and popular. This study aims to explore what and how factors influence members' knowledge contribution behavior in social knowledge communities from the perspective of social distance.

Design/methodology/approach

Based on the theory of reciprocity and on the theory of self-efficacy, hypotheses and research models are proposed. In the empirical study, WeChat learning group is selected as the research case. The empirical investigation (N = 244) collects research data through questionnaires.

Findings

I-intention and we-intention both have positive influence on members' knowledge contribution behavior. Knowledge self-efficacy positively moderates the influence of we-intention and affects knowledge contribution behavior. In addition, I-intention is positively affected by expected knowledge benefit, expected emotional benefit and expected image benefit, while costs have no effect. We-intention is positively influenced by affective commitment, continuance commitment and normative commitment in relationship strength, as well as affiliation to the contributing climate.

Originality/value

This paper aims to discuss I-intention, we-intention, and their roles in members' knowledge contribution behavior. It is a beneficial development for existing research to combine the characteristics of new style communities with systematical analysis of knowledge contribution behavior. Findings may provide enlightenment to the social knowledge community on diversity development and differentiated marketing strategies.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

To view the access options for this content please click here
Article
Publication date: 29 June 2020

Wenming Cheng, Hui Wang, Min Zhang and Run Du

The purpose of this paper is to propose an improved proportional topology optimization (IPTO) algorithm for tackling the stress-constrained minimum volume optimization…

Abstract

Purpose

The purpose of this paper is to propose an improved proportional topology optimization (IPTO) algorithm for tackling the stress-constrained minimum volume optimization problem, which can meet the requirements that are to get rid of the problems of numerical derivation and sensitivity calculation involved in the process of obtaining sensitivity information and overcome the drawbacks of the original proportional topology optimization (PTO) algorithm.

Design/methodology/approach

The IPTO algorithm is designed by using the new target material volume update scheme and the new density variable update scheme and by introducing the improved density filter (considering the weighting function based on the Gaussian distribution) and Heaviside-type projection operator on the basis of the PTO algorithm. The effectiveness of the IPTO algorithm is demonstrated by solving the stress-constrained minimum volume optimization problems for two numerical examples and being compared with the PTO algorithm.

Findings

The results of this paper show that the uses of the proposed strategies contribute to improving the optimized results and the performance (such as the ability to obtain accurate solutions, robustness and convergence speed) of the IPTO algorithm. Compared with the PTO algorithm, the IPTO algorithm has the advantages of fast convergence speed, enhancing the ability to obtain accurate solutions and improving the optimized results.

Originality/value

This paper achieved the author’s intended purpose and provided a new idea for solving the stress-constrained optimization problem under the premise of avoiding obtaining sensitivity information.

Details

Engineering Computations, vol. 38 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

To view the access options for this content please click here
Article
Publication date: 12 August 2019

Xiaobin Xu, Minzhou Luo, Zhiying Tan, Min Zhang and Hao Yang

This paper aims to investigate the effect of unknown noise parameters of Kalman filter on velocity and displacement and to enhance the measured accuracy using adaptive…

Abstract

Purpose

This paper aims to investigate the effect of unknown noise parameters of Kalman filter on velocity and displacement and to enhance the measured accuracy using adaptive Kalman filter with particle swarm optimization algorithm.

Design/methodology/approach

A novel method based on adaptive Kalman filter is proposed. Combined with the displacement measurement model, the standard Kalman filtering algorithm is established. The particle swarm optimization algorithm fused with Kalman is used to obtain the optimal noise parameter estimation using different fitness function.

Findings

The simulations and experimental results show that the adaptive Kalman filter algorithm fused with particle swarm optimization can improve the accuracy of the velocity and displacement.

Originality/value

The adaptive Kalman filter algorithm fused with particle swarm optimization can serve as a new method for optimal state estimation of moving target.

Details

Sensor Review, vol. 39 no. 5
Type: Research Article
ISSN: 0260-2288

Keywords

To view the access options for this content please click here
Article
Publication date: 21 January 2021

Xueqing Zhao, Min Zhang and Junjun Zhang

Classifying the types of fabric defects in the textile industry requires a way to effectively detect. The traditional textile fabric defects detection method is human…

Abstract

Purpose

Classifying the types of fabric defects in the textile industry requires a way to effectively detect. The traditional textile fabric defects detection method is human eyes, which performs very low efficiency and high cost. Therefore, how to improve the classification accuracy of textile fabric defects by using current artificial intelligence and to better meet the needs in the textile industry, the purpose of this article is to develop a method to improve the accuracy of textile fabric defects classification.

Design/methodology/approach

To improve the accuracy of textile fabric defects classification, an ensemble learning-based convolutional neural network (CNN) method in terms of textile fabric defects classification (short for ECTFDC) on an enhanced TILDA database is used. ECTFDC first adopts ensemble learning-based model to classify five types of fabric defects from TILDA. Subsequently, ECTFDC extracts features of fabric defects via an ensemble multiple convolutional neural network model and obtains parameters by using transfer learning method.

Findings

The authors applied ECTFDC on an enhanced TILDA database to improve the robustness and generalization ability of the proposed networks. Experimental results show that ECTFDC outperforms the other networks, the precision and recall rates are 97.8%, 97.68%, respectively.

Originality/value

The ensemble convolutional neural network textile fabric defect classification method in this paper can quickly and effectively classify textile fabric defect categories; it can reduce the production cost of textiles and it can alleviate the visual fatigue of inspectors working for a long time.

Details

International Journal of Clothing Science and Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0955-6222

Keywords

1 – 10 of over 9000